Master data preprocessing and modeling techniques with scikit-learn. Build machine learning models like linear regression and decision trees, focusing on data training, testing, and evaluation.

Become a Machine Learning Engineer

In this module, you'll explore preprocessing data using scikit-learn, including techniques such as feature extraction, scaling, discretizing, encoding, dimensionality reduction, and handling missing values. You'll then explore building and implementing machine learning models like linear regression, logistic regression, and decision trees. The module also covers data training, data testing, cross-validation, and model evaluation methods to ensure the accuracy and robustness of your machine learning solutions.

Preprocessing Data

import pandas as pd
from sklearn.impute import SimpleImputer
from sklearn.preprocessing import StandardScaler, OneHotEncoder, KBinsDiscretizer

data = pd.read_csv('data.csv')

# Defining column types
id_col = ['customerID']
num_cols = ['SeniorCitizen', 'tenure', 'MonthlyCharges', 'TotalCharges']
cat_cols = [
    'gender', 'Partner', 'Dependents',
    'PhoneService', 'MultipleLines', 'InternetService',
    'OnlineSecurity', 'OnlineBackup', 'DeviceProtection',
    'TechSupport', 'StreamingTV', 'StreamingMovies',
    'Contract', 'PaperlessBilling', 'PaymentMethod',
    'Churn'
    ]

# Imputation of missing values
imputer = SimpleImputer(strategy='mean')
data[num_cols] = imputer.fit_transform(data[num_cols])

# Encoding
encoder = OneHotEncoder(handle_unknown='error', drop='first')
encoded = encoder.fit_transform(data[cat_cols])
encoded_df = pd.DataFrame(
    encoded.toarray(),
    columns=encoder.get_feature_names(cat_cols)
)
data = pd.concat([data[id_col+num_cols], encoded_df], axis=1)

# Discretizing
discretizer = KBinsDiscretizer(n_bins=3, encode='ordinal')
data[num_cols] = discretizer.fit_transform(data[num_cols])

# Scaling
scaler = StandardScaler()
data[num_cols] = scaler.fit_transform(data[num_cols])

print(data.head())

Follow the instructions for preprocessing data from a csv file.

Set up for Machine Learning with scikit-learn

Preprocessing with Scikit-Learn

Modeling with Scikit-Learn

Conclusion

Solution: Preprocessing